How To Read The Data
While a lot of the data they receive about their customers comes in formats easy for computers to read, much of it comes in a different form. These types of data could be hand written notes that were jotted down as part of a survey, or even correspondence they received from a customer. The problem with this data is computers have difficulty reading it and then translating it into meaningful information for a company to act upon.
Giving The Data Context
Even if a company gains the ability to read data from large reports or survey questions, it will still have to find a way to automatically distinguish what is said in those reports. For example, take the word “bug” that might be found in a report. Most computers could pick this word out of the report, but they will have a hard time distinguishing between a computer bug, a creepy crawly bug or even a VW bug. Because of this limitation, the results from a simple search could give data that is skewed and inaccurate, making it virtually useless.
Big data can be a great tool for companies, but if they fail to put it in the proper context, it will not give them any meaningful insights into their businesses or their customers. Reading and translating the data accurately is the only way to ensure results that can actually be used by a business to enhance its products and improve their customers’ shopping experiences.
There is a huge fear that big data could mean the end of privacy as we know it. While it is true that more and more of your information is being collected, many companies are trying to collect this data in a manner that not only gives them the meaningful insights they need, but also protects your privacy. Software utilized to read this type of data is being designed and optimized to strip out certain types of data in an attempt to limit the privacy risks of customers.
The push of big data has become a trend that almost all companies, small and large, are taking advantage of every day. With the increasing ability of technology to collect massive amounts of data about customers comes a need to create new systems that are smart enough to read and sort through it all and then present it in an organized fashion that can be used to improve products and customer experience. This presentation represents the biggest challenge faced by companies looking to exploit big data, and it must be solved if they ever hope to benefit from the information it can provide.